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                <div id="site-name"><a href="../../sphinx_pages/build/html/index.html">Shark machine learning library</a></div>
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<h3><a id="index_b" name="index_b"></a>- b -</h3><ul>
<li>back()&#160;:&#160;<a class="el" href="classshark_1_1_data_view.html#af00a7bc78ffc60fcacedbe291b4d24e6">shark::DataView&lt; DatasetType &gt;</a></li>
<li>bag_t&#160;:&#160;<a class="el" href="structshark_1_1_reference_vector_guided_selection.html#aa924daa48c07ebab02ad0f09f1775f49">shark::ReferenceVectorGuidedSelection&lt; IndividualType &gt;</a></li>
<li>BarsAndStripes()&#160;:&#160;<a class="el" href="classshark_1_1_bars_and_stripes.html#a4aacf9ae2eb982898f45075e93d584d8">shark::BarsAndStripes</a></li>
<li>Base&#160;:&#160;<a class="el" href="structshark_1_1_merge_budget_maintenance_strategy_3_01_real_vector_01_4_1_1_merging_problem_function.html#a7644115fbbb1839032ab05a546c1d9fe">shark::MergeBudgetMaintenanceStrategy&lt; RealVector &gt;::MergingProblemFunction</a></li>
<li>base()&#160;:&#160;<a class="el" href="classshark_1_1_scaled_kernel.html#ac5c3092e58aaf96feefbe3e51822e78a">shark::ScaledKernel&lt; InputType &gt;</a></li>
<li>baseRate()&#160;:&#160;<a class="el" href="classshark_1_1_binary_layer.html#aaf3d98e2d4e31b3656dc9635e7aeeeeb">shark::BinaryLayer</a></li>
<li>basis()&#160;:&#160;<a class="el" href="classshark_1_1_kernel_expansion.html#a48c4d31664d347f477cfb305a7b98d61">shark::KernelExpansion&lt; InputType &gt;</a></li>
<li>batch()&#160;:&#160;<a class="el" href="group__shark__globals.html#ga73034ee5639176b0d45e1059859d0f0a">shark::Data&lt; Type &gt;</a>, <a class="el" href="classshark_1_1_data_view.html#a4c811224fc77356555fcecfb5b41cb65">shark::DataView&lt; DatasetType &gt;</a>, <a class="el" href="group__shark__globals.html#ga192f5eced10acf38f3ae723a3c400d98">shark::LabeledData&lt; InputT, LabelT &gt;</a></li>
<li>batch_range&#160;:&#160;<a class="el" href="group__shark__globals.html#ga13c4a238cadf7bca226dee7688241a60">shark::Data&lt; Type &gt;</a>, <a class="el" href="group__shark__globals.html#gab3dadfd210c18bfe97b897d25eb49ac8">shark::LabeledData&lt; InputT, LabelT &gt;</a></li>
<li>batch_reference&#160;:&#160;<a class="el" href="group__shark__globals.html#ga79217da1dd034aa18bc553f483e9449c">shark::Data&lt; Type &gt;</a>, <a class="el" href="group__shark__globals.html#ga6dcbd080f9f9ab3fa3e1e90ba7ca9dc8">shark::LabeledData&lt; InputT, LabelT &gt;</a></li>
<li>batches()&#160;:&#160;<a class="el" href="group__shark__globals.html#ga4edf9849713708253a4d1f2d31e6187b">shark::Data&lt; Type &gt;</a>, <a class="el" href="group__shark__globals.html#ga6c3b7d09e870412534ef27988b950fc6">shark::LabeledData&lt; InputT, LabelT &gt;</a></li>
<li>BatchInputType&#160;:&#160;<a class="el" href="classshark_1_1_abstract_clustering.html#a6865af40b0cab718706e9360b29f2a2c">shark::AbstractClustering&lt; InputT &gt;</a>, <a class="el" href="classshark_1_1_abstract_kernel_function.html#adbf700c2ece7236c70cef4b88777a733">shark::AbstractKernelFunction&lt; InputTypeT &gt;</a>, <a class="el" href="classshark_1_1_abstract_metric.html#a3ed2427fcee73de8368e0e24ce61cada">shark::AbstractMetric&lt; InputTypeT &gt;</a>, <a class="el" href="classshark_1_1_abstract_model.html#a518304e95092673b7b6438cace052ef6">shark::AbstractModel&lt; InputTypeT, OutputTypeT, ParameterVectorType &gt;</a>, <a class="el" href="classshark_1_1_abstract_nearest_neighbors.html#a246b7524f57646d1d830e03c05773824">shark::AbstractNearestNeighbors&lt; InputType, LabelType &gt;</a>, <a class="el" href="classshark_1_1_a_r_d_kernel_unconstrained.html#aa226c405186bb9ef80b64e4ef994155f">shark::ARDKernelUnconstrained&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_c_a_r_tree.html#aaf167bca3b83a14d3fbc520496b3a30d">shark::CARTree&lt; LabelType &gt;</a>, <a class="el" href="classshark_1_1_classifier.html#ae56c82feb436eb83115298ba4fd0c89e">shark::Classifier&lt; Model &gt;</a>, <a class="el" href="classshark_1_1_clustering_model.html#a5a8884d748c8b0c9469c9a9fa8a89395">shark::ClusteringModel&lt; InputT, OutputT &gt;</a>, <a class="el" href="classshark_1_1_concatenated_model.html#a40ecc555741fa16be502dea0b6558a74">shark::ConcatenatedModel&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_conv2_d_model.html#ae73b28ed0cf6fa128617f5ec57890362">shark::Conv2DModel&lt; VectorType, ActivationFunction &gt;</a>, <a class="el" href="classshark_1_1_dropout_layer.html#a8f6384ab6da747494308094f61dcb518">shark::DropoutLayer&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_gaussian_rbf_kernel.html#a7d064811cbd4b5b0794a52ac6db459df">shark::GaussianRbfKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_hard_clustering_model.html#a71f92bc1bc376fd97323cda7e13a27b6">shark::HardClusteringModel&lt; InputT &gt;</a>, <a class="el" href="classshark_1_1_hierarchical_clustering.html#a458996c3186855b3f526d3ea6cb5619d">shark::HierarchicalClustering&lt; InputT &gt;</a>, <a class="el" href="classshark_1_1_kernel_expansion.html#a651c84963d3935af5324530e1722830b">shark::KernelExpansion&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_linear_kernel.html#a7670d367e5567de155331a8777ca5989">shark::LinearKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_linear_model.html#ac853fcaa6620e0eaf0e7c7f81a31b646">shark::LinearModel&lt; InputType, ActivationFunction &gt;</a>, <a class="el" href="classshark_1_1_missing_features_kernel_expansion.html#acc2b882befd9e12e1465bc845d45ebd2">shark::MissingFeaturesKernelExpansion&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_model_kernel.html#ad8dc6e6fd8567cda2ad5f220beb31bbd">shark::ModelKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_monomial_kernel.html#af6fcaf4018d03f30ff9e251418c778f0">shark::MonomialKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_neuron_layer.html#acf10127eec7ebc5ce7fa1c5705a7b879">shark::NeuronLayer&lt; NeuronType, VectorType &gt;</a>, <a class="el" href="classshark_1_1_normalized_kernel.html#ae982a2e874a2d918533a8f663faf0ecb">shark::NormalizedKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_normalizer.html#a7408418eee8abc1658985875bc4bd1ab">shark::Normalizer&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_one_versus_one_classifier.html#a62a08462043b510e68dac7ae646156b2">shark::OneVersusOneClassifier&lt; InputType, VectorType &gt;</a>, <a class="el" href="classshark_1_1_point_set_kernel.html#aea5b62dc8038d6ad9b70f4dde9c2e1d3">shark::PointSetKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_polynomial_kernel.html#a7e8c12320edf40b81320d4c1eb64ee25">shark::PolynomialKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_pooling_layer.html#af1c3bf01a5867b9c2cea965b3f5e5d2b">shark::PoolingLayer&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_product_kernel.html#aa90803815be279450eebc269666342d0">shark::ProductKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_r_b_m.html#ae23bef32feaf5bf153d2fc25fca42557">shark::RBM&lt; VisibleLayerT, HiddenLayerT, randomT &gt;</a>, <a class="el" href="classshark_1_1_resize_layer.html#a0cfbefe78f78e071d3b9db899b3c3f29">shark::ResizeLayer&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_scaled_kernel.html#ade088748ce9c72aadd6218534d0b918f">shark::ScaledKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_simple_nearest_neighbors.html#ad878c943fb9776f495b796d718e3a099">shark::SimpleNearestNeighbors&lt; InputType, LabelType &gt;</a>, <a class="el" href="classshark_1_1_tree_nearest_neighbors.html#a00707a24f04878d9c64546366e3cccea">shark::TreeNearestNeighbors&lt; InputType, LabelType &gt;</a>, <a class="el" href="classshark_1_1_weighted_sum_kernel.html#afe31030a33669b789e1d92d56da07882">shark::WeightedSumKernel&lt; InputType &gt;</a></li>
<li>BatchLabelType&#160;:&#160;<a class="el" href="classshark_1_1_absolute_loss.html#ad37c06e8490fc84fdc8d2018d3679a9e">shark::AbsoluteLoss&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_abstract_cost.html#ae76592e18c367f68e9456e76acc35c03">shark::AbstractCost&lt; LabelT, OutputT &gt;</a>, <a class="el" href="classshark_1_1_abstract_loss.html#a6e6cc93c4d6599c219d396dcab81e938">shark::AbstractLoss&lt; LabelT, OutputT &gt;</a>, <a class="el" href="classshark_1_1_squared_loss.html#ad4f8ad15cf428d7ed9e128f501a10964">shark::SquaredLoss&lt; OutputType, LabelType &gt;</a>, <a class="el" href="classshark_1_1_squared_loss_3_01_output_type_00_01unsigned_01int_01_4.html#aa0b3345ab9e670e41a9018746a333e76">shark::SquaredLoss&lt; OutputType, unsigned int &gt;</a>, <a class="el" href="classshark_1_1_zero_one_loss.html#ab43603f1f7774b72b2178946e6485eeb">shark::ZeroOneLoss&lt; LabelType, OutputType &gt;</a>, <a class="el" href="classshark_1_1_zero_one_loss_3_01unsigned_01int_00_01blas_1_1vector_3_01_float_01_4_01_4.html#a420c0aeacacb743e68ba44e6f7ef6005">shark::ZeroOneLoss&lt; unsigned int, blas::vector&lt; Float &gt; &gt;</a></li>
<li>BatchOutputType&#160;:&#160;<a class="el" href="classshark_1_1_absolute_loss.html#a06f9c5158cce6fb93ad9d00b484d29d4">shark::AbsoluteLoss&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_abstract_clustering.html#a0857a0698bf699be93ccf595406bdf96">shark::AbstractClustering&lt; InputT &gt;</a>, <a class="el" href="classshark_1_1_abstract_cost.html#a34c29a41e3dc317b2c97a49e2dbe5da4">shark::AbstractCost&lt; LabelT, OutputT &gt;</a>, <a class="el" href="classshark_1_1_abstract_loss.html#ac3a1a01831f11b5357d6005837ac245b">shark::AbstractLoss&lt; LabelT, OutputT &gt;</a>, <a class="el" href="classshark_1_1_abstract_model.html#aa0c72e230b9a1324c95ba8ac0b07ba13">shark::AbstractModel&lt; InputTypeT, OutputTypeT, ParameterVectorType &gt;</a>, <a class="el" href="classshark_1_1_c_a_r_tree.html#aa2ae0547dd93ae91396f155ac603d698">shark::CARTree&lt; LabelType &gt;</a>, <a class="el" href="classshark_1_1_classifier.html#a997346948fcd63ecfee7be139637c2be">shark::Classifier&lt; Model &gt;</a>, <a class="el" href="classshark_1_1_clustering_model.html#a1deee76d6cb1728c6b7d4e1eeef078f2">shark::ClusteringModel&lt; InputT, OutputT &gt;</a>, <a class="el" href="classshark_1_1_concatenated_model.html#a8ebf5d7a639b9bad3c97155457ab07b9">shark::ConcatenatedModel&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_conv2_d_model.html#a3d8e691008283fe9b6a68bd542c86fc0">shark::Conv2DModel&lt; VectorType, ActivationFunction &gt;</a>, <a class="el" href="classshark_1_1_dropout_layer.html#a7a1a78269526acd2e0a42b1959bd3e88">shark::DropoutLayer&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_hard_clustering_model.html#a25dc4fbdb9e66c4924d26d96305886e1">shark::HardClusteringModel&lt; InputT &gt;</a>, <a class="el" href="classshark_1_1_hierarchical_clustering.html#af8ffb5865a040974a11cdd27f0c39ab3">shark::HierarchicalClustering&lt; InputT &gt;</a>, <a class="el" href="classshark_1_1_kernel_expansion.html#a3d47bea3d1bb6b1c5044c9208f1dfd09">shark::KernelExpansion&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_linear_model.html#af91aadf2cf38896d43d79bf1caa7218d">shark::LinearModel&lt; InputType, ActivationFunction &gt;</a>, <a class="el" href="classshark_1_1_missing_features_kernel_expansion.html#afa1fd94574199968f74a3ebf54792e56">shark::MissingFeaturesKernelExpansion&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_neuron_layer.html#ac37aa324e1d18b80f85897965120b736">shark::NeuronLayer&lt; NeuronType, VectorType &gt;</a>, <a class="el" href="classshark_1_1_normalizer.html#a6ab92ed11265d2d649ebf3856e1462a9">shark::Normalizer&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_one_versus_one_classifier.html#ac67af1a218f9e7e3fef40649d402a449">shark::OneVersusOneClassifier&lt; InputType, VectorType &gt;</a>, <a class="el" href="classshark_1_1_pooling_layer.html#a66639a814abf022b6935327f880f6f31">shark::PoolingLayer&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_r_b_m.html#a49d157ed652e935efdf9e64671a2cb46">shark::RBM&lt; VisibleLayerT, HiddenLayerT, randomT &gt;</a>, <a class="el" href="classshark_1_1_resize_layer.html#a83d970b4538adad3aa095e08ca639c9e">shark::ResizeLayer&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_squared_loss.html#ad38b488ba8cd4842e9423bf4d632f6ae">shark::SquaredLoss&lt; OutputType, LabelType &gt;</a>, <a class="el" href="classshark_1_1_squared_loss_3_01_output_type_00_01unsigned_01int_01_4.html#ab92e8fb56e9a07ceb63e82a73f13e72b">shark::SquaredLoss&lt; OutputType, unsigned int &gt;</a>, <a class="el" href="classshark_1_1_zero_one_loss.html#adac2c5c0e4fd170d44d604e663ec30d6">shark::ZeroOneLoss&lt; LabelType, OutputType &gt;</a>, <a class="el" href="classshark_1_1_zero_one_loss_3_01unsigned_01int_00_01blas_1_1vector_3_01_float_01_4_01_4.html#aa2436ce8cb86ce9f7d88622a452affdb">shark::ZeroOneLoss&lt; unsigned int, blas::vector&lt; Float &gt; &gt;</a></li>
<li>batchSize()&#160;:&#160;<a class="el" href="classshark_1_1_energy_storing_tempered_markov_chain.html#a862d3a6d440f46551a810fafb39402c6">shark::EnergyStoringTemperedMarkovChain&lt; Operator &gt;</a>, <a class="el" href="classshark_1_1_markov_chain.html#af08ad5f1c8a58c1c8e8981f480a560ba">shark::MarkovChain&lt; Operator &gt;</a>, <a class="el" href="classshark_1_1_m_n_i_s_t.html#ae8a337edde7be1fa79586d97dd322aec">shark::MNIST</a>, <a class="el" href="classshark_1_1_tempered_markov_chain.html#a98e24129ec94644d01b644006bcdae91">shark::TemperedMarkovChain&lt; Operator &gt;</a></li>
<li>begin()&#160;:&#160;<a class="el" href="structshark_1_1_batch_3_01shark_1_1blas_1_1compressed__vector_3_01_t_01_4_01_4.html#a8e061f102977183d90c6da291ab7fcd0">shark::Batch&lt; shark::blas::compressed_vector&lt; T &gt; &gt;</a>, <a class="el" href="classshark_1_1_data_view.html#a3e7c59021eff4745396ed9951c2f05ca">shark::DataView&lt; DatasetType &gt;</a>, <a class="el" href="classshark_1_1_evaluation_archive.html#ab99cdfba0518a01012dbc818a87c495c">shark::EvaluationArchive&lt; PointType, ResultT &gt;</a>, <a class="el" href="classshark_1_1statistics_1_1_result_table.html#a45c52fe99fcb6389ea30d6541efec2fd">shark::statistics::ResultTable&lt; Parameter &gt;</a>, <a class="el" href="structshark_1_1statistics_1_1_statistics.html#aa6adcdd673621c217d95aa93c0f61dac">shark::statistics::Statistics&lt; Parameter &gt;</a>, <a class="el" href="structshark_1_1_weighted_data_batch.html#a98dd827f038cb5b040270fe7b04dd0bf">shark::WeightedDataBatch&lt; DataBatchType, WeightBatchType &gt;</a></li>
<li>beta()&#160;:&#160;<a class="el" href="classshark_1_1_energy_storing_tempered_markov_chain.html#ab07c1453c6cadb92927acfcf4354c5b0">shark::EnergyStoringTemperedMarkovChain&lt; Operator &gt;</a>, <a class="el" href="structshark_1_1_radius_margin_quotient_1_1_result.html#a3e738702ef77426ccfd6dfc05fc9716d">shark::RadiusMarginQuotient&lt; InputType, CacheType &gt;::Result</a>, <a class="el" href="classshark_1_1_tempered_markov_chain.html#affbe3936aa5f1429657be37e260abce7">shark::TemperedMarkovChain&lt; Operator &gt;</a></li>
<li>beta1()&#160;:&#160;<a class="el" href="classshark_1_1_adam.html#afcabef3366290b075d51294876732613">shark::Adam&lt; SearchPointType &gt;</a></li>
<li>beta2()&#160;:&#160;<a class="el" href="classshark_1_1_adam.html#a13b7618dea5584ffd886c15858d02888">shark::Adam&lt; SearchPointType &gt;</a></li>
<li>bias()&#160;:&#160;<a class="el" href="classshark_1_1_binary_layer.html#a103a1cdde7c111a6cbb3b059bf3e61df">shark::BinaryLayer</a>, <a class="el" href="classshark_1_1_bipolar_layer.html#abc3c1b86b1ad2692712c0e4b34f0d15d">shark::BipolarLayer</a>, <a class="el" href="classshark_1_1_classifier.html#ae97fca135ea08ed2c8e60d01b3aad117">shark::Classifier&lt; Model &gt;</a>, <a class="el" href="classshark_1_1_gaussian_layer.html#a877687dcf1eb19c17c0a2c941e7bf0a5">shark::GaussianLayer</a></li>
<li>BiasSolver()&#160;:&#160;<a class="el" href="classshark_1_1_bias_solver.html#afafb19ac1d26e80b42df574068906ef0">shark::BiasSolver&lt; Matrix &gt;</a></li>
<li>BiasSolverSimplex()&#160;:&#160;<a class="el" href="classshark_1_1_bias_solver_simplex.html#a63c458c8a8636282d49b4f1cba6cbd00">shark::BiasSolverSimplex&lt; Matrix &gt;</a></li>
<li>binary()&#160;:&#160;<a class="el" href="classshark_1_1_one_versus_one_classifier.html#aa14ccce9b2bb1004e0d3165ca3c24094">shark::OneVersusOneClassifier&lt; InputType, VectorType &gt;</a></li>
<li>binaryToInt()&#160;:&#160;<a class="el" href="structshark_1_1_hypervolume_calculator_m_d_h_o_y.html#a6c778375e99721c6553b720de8ba2323">shark::HypervolumeCalculatorMDHOY</a></li>
<li>BinaryTree()&#160;:&#160;<a class="el" href="classshark_1_1_binary_tree.html#a50b781f4203ea4d3a9e1dc60a52bec4e">shark::BinaryTree&lt; InputT &gt;</a></li>
<li>BitflipMutator()&#160;:&#160;<a class="el" href="structshark_1_1_bitflip_mutator.html#afbc4c1396a28cc2b8f26317af44e2625">shark::BitflipMutator</a></li>
<li>BlockMatrix2x2()&#160;:&#160;<a class="el" href="classshark_1_1_block_matrix2x2.html#a4503961134dc4428dd9675c5c8289797">shark::BlockMatrix2x2&lt; Matrix &gt;</a></li>
<li>BlockMatrixType&#160;:&#160;<a class="el" href="classshark_1_1_epsilon_svm_trainer.html#ae9818f09ebb48a69b1b28d3042da56da">shark::EpsilonSvmTrainer&lt; InputType, CacheType &gt;</a></li>
<li>BOOST_SERIALIZATION_SPLIT_MEMBER()&#160;:&#160;<a class="el" href="classshark_1_1_i_serializable.html#a4560a94e8f4908fe8627e41e7d965735">shark::ISerializable</a></li>
<li>BOOST_STATIC_CONSTANT()&#160;:&#160;<a class="el" href="structboost_1_1serialization_1_1tracking__level_3_01shark_1_1_typed_flags_3_01_t_01_4_01_4.html#a1c7330570427386ec3c3ed5bcc5490a9">boost::serialization::tracking_level&lt; shark::TypedFlags&lt; T &gt; &gt;</a>, <a class="el" href="structboost_1_1serialization_1_1tracking__level_3_01std_1_1vector_3_01_t_01_4_01_4.html#a11bb9f9d1029c8ef233c618863b71281">boost::serialization::tracking_level&lt; std::vector&lt; T &gt; &gt;</a>, <a class="el" href="group__shark__globals.html#ga425774be1ecd7d42c890d68fe58c3aa1">shark::Data&lt; Type &gt;</a>, <a class="el" href="classshark_1_1_weighted_labeled_data.html#af260c63209f6881849b736c91fc000d3">shark::WeightedLabeledData&lt; InputT, LabelT &gt;</a>, <a class="el" href="classshark_1_1_weighted_unlabeled_data.html#ad6c78becf3a0a703a506f17d9535e0b9">shark::WeightedUnlabeledData&lt; DataT &gt;</a></li>
<li>boundingBox&#160;:&#160;<a class="el" href="structshark_1_1_hypervolume_contribution_approximator_1_1_point.html#a51eda5e69958b276c275be215c419f59">shark::HypervolumeContributionApproximator::Point&lt; VectorType &gt;</a></li>
<li>boundingBoxVolume&#160;:&#160;<a class="el" href="structshark_1_1_hypervolume_contribution_approximator_1_1_point.html#a81fc3e2d54ce593ce0574c655599b769">shark::HypervolumeContributionApproximator::Point&lt; VectorType &gt;</a></li>
<li>BoxBasedShrinkingStrategy()&#160;:&#160;<a class="el" href="structshark_1_1_box_based_shrinking_strategy.html#a80dbbcad0a023740c8d0bfa4a6ac4a99">shark::BoxBasedShrinkingStrategy&lt; Problem &gt;</a></li>
<li>BoxConstrainedProblem()&#160;:&#160;<a class="el" href="classshark_1_1_box_constrained_problem.html#a5544fa68b725cb68c8af64b4133a7c74">shark::BoxConstrainedProblem&lt; SVMProblem &gt;</a></li>
<li>BoxConstrainedShrinkingProblem()&#160;:&#160;<a class="el" href="classshark_1_1_box_constrained_shrinking_problem.html#ac8a3920dc82f084fa2bf75df70eb2134">shark::BoxConstrainedShrinkingProblem&lt; Problem &gt;</a></li>
<li>BoxConstraintHandler()&#160;:&#160;<a class="el" href="classshark_1_1_box_constraint_handler.html#ae234333cf7124b58f49a67b2bee42f61">shark::BoxConstraintHandler&lt; Vector &gt;</a></li>
<li>BoxedSVMProblem()&#160;:&#160;<a class="el" href="classshark_1_1_boxed_s_v_m_problem.html#a8646da44427a08f8262f7675bcfdb4b8">shark::BoxedSVMProblem&lt; MatrixT &gt;</a></li>
<li>boxMax()&#160;:&#160;<a class="el" href="classshark_1_1_box_constrained_problem.html#ad2f65f5e6c2917efadd23806ba823ff2">shark::BoxConstrainedProblem&lt; SVMProblem &gt;</a>, <a class="el" href="classshark_1_1_boxed_s_v_m_problem.html#a638209b50fe9c222fe9fe444339018f1">shark::BoxedSVMProblem&lt; MatrixT &gt;</a>, <a class="el" href="classshark_1_1_c_s_v_m_problem.html#a4b1679d10868333bf4d4c8b4b4d37ed6">shark::CSVMProblem&lt; MatrixT &gt;</a>, <a class="el" href="classshark_1_1_general_quadratic_problem.html#a469feeb215ab016a23c930d120071074">shark::GeneralQuadraticProblem&lt; MatrixT &gt;</a>, <a class="el" href="classshark_1_1_svm_problem.html#afc78269e1b3b3f0372018eb3172db25e">shark::SvmProblem&lt; Problem &gt;</a></li>
<li>boxMin()&#160;:&#160;<a class="el" href="classshark_1_1_box_constrained_problem.html#a11b7f562555c6f3718b059eee25bf765">shark::BoxConstrainedProblem&lt; SVMProblem &gt;</a>, <a class="el" href="classshark_1_1_boxed_s_v_m_problem.html#adb721af815d4a5d0ec6a62f8aeb1f562">shark::BoxedSVMProblem&lt; MatrixT &gt;</a>, <a class="el" href="classshark_1_1_c_s_v_m_problem.html#ac5abe1188b5f7a69e12248ddf5cc960f">shark::CSVMProblem&lt; MatrixT &gt;</a>, <a class="el" href="classshark_1_1_general_quadratic_problem.html#aa9f1ae2df5eaaf432872ded870d8787d">shark::GeneralQuadraticProblem&lt; MatrixT &gt;</a>, <a class="el" href="classshark_1_1_svm_problem.html#aeb63064bffd6c4f4ff157a45535bb142">shark::SvmProblem&lt; Problem &gt;</a></li>
<li>budgetMaintenanceStrategy()&#160;:&#160;<a class="el" href="classshark_1_1_kernel_budgeted_s_g_d_trainer.html#aacf277842f28d9d49b1aea197ba710ac">shark::KernelBudgetedSGDTrainer&lt; InputType, CacheType &gt;</a></li>
<li>budgetSize()&#160;:&#160;<a class="el" href="classshark_1_1_kernel_budgeted_s_g_d_trainer.html#a1f1e8961c4e22246f2fe3d023335c571">shark::KernelBudgetedSGDTrainer&lt; InputType, CacheType &gt;</a></li>
<li>buildTree()&#160;:&#160;<a class="el" href="classshark_1_1_k_d_tree.html#a7ca41c2db8a6d814deef326dd0bbfa44">shark::KDTree&lt; InputT &gt;</a>, <a class="el" href="classshark_1_1_k_h_c_tree.html#a96ac23e4df78cfa576aae64ba7600b97">shark::KHCTree&lt; Container, CuttingAccuracy &gt;</a>, <a class="el" href="classshark_1_1_l_c_tree.html#a24332e2c05b6a959b8f98577f83ab88a">shark::LCTree&lt; VectorType, CuttingAccuracy &gt;</a></li>
<li>buildType()&#160;:&#160;<a class="el" href="classshark_1_1_shark.html#a468b025010bb4cbced92b7362f916d3a">shark::Shark</a></li>
<li>bUnshrinked&#160;:&#160;<a class="el" href="classshark_1_1_qp_mc_box_decomp.html#aca3e51d1597fbb5e54f7a0e88c96a7dc">shark::QpMcBoxDecomp&lt; Matrix &gt;</a>, <a class="el" href="classshark_1_1_qp_mc_simplex_decomp.html#ae4356261aaf70b6569308fa13f01a56a">shark::QpMcSimplexDecomp&lt; Matrix &gt;</a></li>
</ul>
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